Redshift Performance Problem

I have call center data that I pull in through inContact and I need to add a date field from a date/time field in order to not have problems with time. To do this, I've made a redshift flow that selects all the fields and truncates the date/time field to a date field:


Select field1, field2, ...,

TRUNC(CONVERT_TIMEZONE('UTC','America/Chicago',"contactStart")) AS contactStartdate

from table


Since the data comes in as UTC, I first convert it to central and the truncate it. That way I get the correct date out of the stamp. The table has 52 columns and usually about 3000-4000 rows being replaced every 15min.


My problem is I need to update this dataset every 15min, but the redshift query sometime takes 30 seconds or over 10-15min. Any ideas on what is going on/how I can get it to consistently run for only 30 seconds?


Best Answer

  • DDalt
    Answer ✓

    I was curious about Redshift run times being inconsistent and posed a question on DOJO day. Here is the question and response:



    I tested one of my data flows that had the same requirements you have (select all columns, but convert the timestamps) using both Redshift and MySQL and I did see both more consistent run times and a lower 30 day average duration when using MySQL.


    So you might want to make a copy of your data flow & convert it to MySQL to see if you can achieve the results you are looking for.